Triple

T34094533
Position Surface form Disambiguated ID Type / Status
Subject Strand Road, Kolkata E874387 entity
Predicate near P350 FINISHED
Object Kolkata riverfront
The Kolkata riverfront is a scenic stretch along the Hooghly River known for its historic ghats, promenades, and views of iconic bridges like Howrah and Vidyasagar Setu.
E2082589 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Kolkata riverfront | Statement: [Strand Road, Kolkata, near, Kolkata riverfront]
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Kolkata riverfront
Triple: [Strand Road, Kolkata, near, Kolkata riverfront]
Generated description
The Kolkata riverfront is a scenic stretch along the Hooghly River known for its historic ghats, promenades, and views of iconic bridges like Howrah and Vidyasagar Setu.

Provenance (5 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69f349a735208190a1dbfb1c2a121059 completed April 30, 2026, 12:23 p.m.
NER Named-entity recognition batch_69f70c5676648190b2bee263bbc8ec7d completed May 3, 2026, 8:50 a.m.
NED1 Entity disambiguation (via context triple) batch_6a36b762b65c8190a840730b035d3912 completed June 20, 2026, 3:53 p.m.
NEDg Description generation batch_6a36b804ef888190b32868e5dcfd190c completed June 20, 2026, 3:55 p.m.
NED2 Entity disambiguation (via description) batch_6a36b88c59788190b825ae7220be3b1a completed June 20, 2026, 3:58 p.m.
Created at: May 1, 2026, 1:52 a.m.